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Vibedata

Build something that is not there yet

Produce the trial balance and close pack as code

  • When the close pack is rebuilt by hand in a spreadsheet every period.
  • When last quarter's trial balance can't be reproduced because nothing kept the inputs that produced it.

Build the trial balance by account and fiscal period, opening through closing, with debits-equal-credits tests, late-posting flags, and a period-lock check as committed dbt models. Covers the balances and their proof, not the narrative commentary in the pack.

Area
Transformation
Runs on
  • Microsoft Fabric Lakehouse
  • Microsoft Fabric Warehouse
  • MotherDuck
  • DuckDB
Built with
  • dbt
Domain
Finance
Industry
Banking, Manufacturing, Retail
Readiness
SupportedEverything this Recipe composes runs today, without a case that proves this exact shape.

Sample This Recipe has not been materialized in the Cookbook repository yet. Its trigger, description, prompt, agent guidance and acceptance conditions, and the explanation below, are prototype drafts. Its name, job, area and readiness come from the reconciled Cookbook seed snapshot. Readiness is a separate question from this one: it says whether the capability exists, not whether the writing has been reviewed.

Use this Recipe

Use the VibeData Recipe `finance-trial-balance-close` at https://getvibedata.ai/cookbook/finance-trial-balance-close Read the Recipe and execute it in the context of the current Intent.

Recipe id finance-trial-balance-close · Not yet materialized in the Cookbook repository, so the pointer addresses this page.

Verified by

What has to be observably true before this Recipe is finished.

  • debits equal credits for every period and every journal
  • each period's closing balance equals the next period's opening balance
  • entries posted after the soft-close date are flagged rather than silently included
  • a change to a hard-closed period fails the build instead of passing as a warning
Recipe promptThe task specification the agent reads. Reference only — it is not what you copy.
Deliver: Produce the trial balance and close pack as code.

Build the trial balance by account and fiscal period, opening through closing, with debits-equal-credits tests, late-posting flags, and a period-lock check as committed dbt models. Covers the balances and their proof, not the narrative commentary in the pack.

Execute inside the current Intent. Its Domain, repository, platform, environment and attached sources are the context for this work — read them rather than asking for them.

The work is done when:
- debits equal credits for every period and every journal
- each period's closing balance equals the next period's opening balance
- entries posted after the soft-close date are flagged rather than silently included
- a change to a hard-closed period fails the build instead of passing as a warning

Report the evidence for each condition above with the result. A condition you cannot meet is something to say, not something to work around.
Agent guidanceHow the agent approaches the work, and what it will not do.

Profile the inputs the grain, joins and measures actually depend on before proposing a model. Put the design up for review — grain first — then build in an isolated copy with tests and documentation landing beside the model rather than after it.

Composes

  • dbt model authoring and layering
  • dbt in the project
  • isolated-copy execution and gate verification

Asks first

Semantic decisions the Intent cannot supply. Never context Studio already holds.

  • which Fabric target this work lands on, when the Domain carries both a Lakehouse and a Warehouse
  • the grain the requester expects, where the request leaves it open to more than one reading

Guardrails

  • Build in an isolated copy. Production is read, never written.

What you need

  • Microsoft Fabric Lakehouse, Microsoft Fabric Warehouse, MotherDuck, or DuckDB.
  • A dbt project you can build, and read access to the models it starts from.
  • dbt in the project, or the intent to add it.

How it goes

  1. State the outcome in one sentence, in the language the request arrived in.
  2. Let it profile the inputs the grain, the joins and the measures actually depend on.
  3. Review the design. Disagreeing about grain here costs a sentence; after the model exists it costs a rewrite.
  4. Let it build in an isolated copy, with the tests and the documentation landing beside the model rather than after it.
  5. Read the acceptance conditions against the run.

What you end up with

The deliverable, in your own repository, as transformation work a reviewer who knows the project reads as native to it. Alongside it, the evidence for every one of the acceptance conditions above — which is the part that is still there in three weeks when somebody asks.